Absorbance Lab Report
The Effect of Concentration on Absorbance
Background Information The purpose of the “Determining Solution ‘Concentration’ Using A Spectrophotometer” lab was to use a spectrophotometer to find the relationship of concentration and absorbance obeying the Beer-Lambert law, which states concentration and absorbance are directly related, to then further determine the concentration of three unknown solutions. With the assumption that the solutions obey the Beer-Lambert law it is predicted that as concentration increases, absorbance will increase as well. A spectrophotometer is a device that uses a light source of all visible light along with ultraviolet and infrared ranges. Diffraction grating then separates the light by wavelength. The light …show more content…
This hypothesis was clearly supported through data in this lab. This is because the standard graph shows the direct relationship between the two. Also, the linear fit equation was able to be used to accurately calculate the molarity of three unknown solutions. There could be many areas of further investigation of this lab. Different solutions, such as gatorade or soda, instead of food coloring can be used to see if they display the same results. The information from this lab can be applied in more advanced research such as determining concentration of different molecules or cells, which affect life. The results do make a lot of sense. They follow the Beer-Lambert law if terms of the concentration having a direct relationship with absorbance. The linear fit equation and correlation coefficient are great forms of data because it tells how accurately procedures were done in the lab and how they fit the hypothesis. If the slope was negative, that would clearly present a problem to the Beer-Lambert law. If the y-intercept is far off from 0, that presents an issue in data because it is supposed to be at 0. The correlation coefficient displays how directly related the dependent and independent variables are. For this lab the slope must be positive, the y-intercept needs to be close to zero and the correlation coefficient needs to be close to one. Therefore, this data makes sense because it was expected by being explained using the Beer-Lambert
Background Information The purpose of the “Determining Solution ‘Concentration’ Using A Spectrophotometer” lab was to use a spectrophotometer to find the relationship of concentration and absorbance obeying the Beer-Lambert law, which states concentration and absorbance are directly related, to then further determine the concentration of three unknown solutions. With the assumption that the solutions obey the Beer-Lambert law it is predicted that as concentration increases, absorbance will increase as well. A spectrophotometer is a device that uses a light source of all visible light along with ultraviolet and infrared ranges. Diffraction grating then separates the light by wavelength. The light …show more content…
This hypothesis was clearly supported through data in this lab. This is because the standard graph shows the direct relationship between the two. Also, the linear fit equation was able to be used to accurately calculate the molarity of three unknown solutions. There could be many areas of further investigation of this lab. Different solutions, such as gatorade or soda, instead of food coloring can be used to see if they display the same results. The information from this lab can be applied in more advanced research such as determining concentration of different molecules or cells, which affect life. The results do make a lot of sense. They follow the Beer-Lambert law if terms of the concentration having a direct relationship with absorbance. The linear fit equation and correlation coefficient are great forms of data because it tells how accurately procedures were done in the lab and how they fit the hypothesis. If the slope was negative, that would clearly present a problem to the Beer-Lambert law. If the y-intercept is far off from 0, that presents an issue in data because it is supposed to be at 0. The correlation coefficient displays how directly related the dependent and independent variables are. For this lab the slope must be positive, the y-intercept needs to be close to zero and the correlation coefficient needs to be close to one. Therefore, this data makes sense because it was expected by being explained using the Beer-Lambert